Contact PD/PI: Vladimirov, Vladimir I Abstract: The objective of this proposal is to investigate the biological mechanisms by which microRNAs (miRNAs) contribute to major depressive disorder (MDD). MDD is a severe mental disorder and the single most common risk factor for suicide. Recent genome-wide association studies (GWAS) of large samples of MDD have for the first time identified robust genetic associations with major depression. However, the biological mechanisms by which these increase the risk for major depression are still unknown. Additionally, most genetic variants associated with MDD fall outside of the protein coding transcriptome, suggesting that their functional impact is likely to affect gene expression levels rather than protein structure. MiRNA are highly expressed in the brain and were shown to play an important role in the pathology of psychiatric disorders including MDD and their canonical functions are to control gene expression levels. Despite their importance, however, profiling of miRNA expression in large postmortem brain samples for various neuropsychiatric disorders including MDD across different brain regions currently do not yet exist. Thus, in this application we propose to use miRNA sequencing to assess miRNA expression in one of the largest postmortem brain samples of major depression in the world. The sample has been extensively characterized clinically, genetically, and molecularly and provides a unique resource for examining the neurobiological mechanisms by which genetic factors contribute to major depression directly in the primary affected tissue. Our miRNA data will be integrated with an ongoing RNA sequencing data generated in the same subjects to identify miRNA/mRNA pairs with important disease functions. Our aims are to: 1) carry out miRNA sequencing of the subgenual anterior cingulate cortex (sACC) and amygdala in 200 recurrent MDD cases and 200 matched controls, 2) test whether genome-wide significant SNPs from GWAS of MDD are associated with miRNA expression across these key regions of the brain, 3) identify miRNA whose expression is associated with major depression and suicide and perform a series of univariate, multivariate (network), and data integration analyses to further elucidate miRNA role in the neuropathology of MDD, 4) replicate our top miRNA (FDR ?5%) in an independently ascertain postmortem brain sample of 50 MDD cases and 50 matched controls. In aim 4 we will also perform series of exploratory analyses to identify the cellular mechanism by which risk MDD variants affect miRNA/mRNA interactions. We hypothesize that a major mechanism contributing to the etiology of major depression is through the ability of risk MDD variants to affect miRNA expression and functions. By explicating the mechanisms by which risk MDD variants lead to increase risk of major depression, we will provide novel targets for intervention in the disease process and, therefore, a more rational basis for improved treatments.